Google Cloud Certified Professional-Cloud-Architect完全版問題集には無料PDF問題で合格させる
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Google認定プロフェッショナル-クラウドアーキテクト（GCP）になるには、Professional-Cloud-Architect試験に合格する必要があります。この認定資格は、GCPサービスの深い理解と、堅牢で安全かつスケーラブルなソリューションを設計、開発、管理する能力を持つ個人を対象としています。認定試験は、クラウドアーキテクチャ、インフラストラクチャ、データストレージ、ネットワーキング、セキュリティ、アプリケーション開発など、幅広いトピックをカバーしています。この認定資格は、プロフェッショナルがGCPを使用したクラウドソリューションを設計、実装するために必要なスキルと知識を持っていることを証明するものであり、クラウドコンピューティング業界でのより良い就職機会や高い給与につながることがあります。
質問 # 115
During a high traffic portion of the day, one of your relational databases crashes, but the replica is never promoted to a master. You want to avoid this in the future.
What should you do?
- A. Choose larger instances for your database
- B. Create snapshots of your database more regularly
- C. Use a different database
- D. Implement routinely scheduled failovers of your databases
正解：B
解説：
Explanation/Reference:
Explanation:
Take regular snapshots of your database system.
If your database system lives on a Compute Engine persistent disk, you can take snapshots of your system each time you upgrade. If your database system goes down or you need to roll back to a previous version, you can simply create a new persistent disk from your desired snapshot and make that disk the boot disk for a new Compute Engine instance. Note that, to avoid data corruption, this approach requires you to freeze the database system's disk while taking a snapshot.
Reference: https://cloud.google.com/solutions/disaster-recovery-cookbook
質問 # 116
For this question, refer to the Dress4Win case study.
As part of Dress4Win's plans to migrate to the cloud, they want to be able to set up a managed logging and monitoring system so they can handle spikes in their traffic load. They want to ensure that:
* The infrastructure can be notified when it needs to scale up and down to handle the ebb and flow of usage throughout the day
* Their administrators are notified automatically when their application reports errors.
* They can filter their aggregated logs down in order to debug one piece of the application across many hosts Which Google StackDriver features should they use?
- A. Monitoring, Trace, Debug, Logging
- B. Monitoring, Logging, Debug, Error Report
- C. Monitoring, Logging, Alerts, Error Reporting
- D. Logging, Alerts, Insights, Debug
正解：B
解説：
Topic 2, TerramEarth
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day. TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
* Decrease unplanned vehicle downtime to less than 1 week, without increasing the cost of carrying surplus inventory
* Support the dealer network with more data on how their customers use their equipment IP better position new products and services.
* Have the ability to partner with different companies-especially with seed and fertilizer suppliers in the fast-growing agricultural business-to create compelling joint offerings for their customers CEO Statement We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
質問 # 117
A lead software engineer tells you that his new application design uses websockets and HTTP sessions that are not distributed across the web servers. You want to help him ensure his application will run property on Google Cloud Platform. What should you do?
- A. Review the encryption requirements for websocket connections with the security team.
- B. Meet with the cloud operations team and the engineer to discuss load balancer options.
- C. Help the engineer to convert his websocket code to use HTTP streaming.
- D. Help the engineer redesign the application to use a distributed user session service that does not rely on websockets and HTTP sessions.
正解：B
解説：
Google Cloud Platform (GCP) HTTP(S) load balancing provides global load balancing for HTTP(S) requests destined for your instances.
The HTTP(S) load balancer has native support for the WebSocket protocol.
Incorrect Answers:
A: HTTP server push, also known as HTTP streaming, is a client-server communication pattern that sends information from an HTTP server to a client asynchronously, without a client request. A server push architecture is especially effective for highly interactive web or mobile applications, where one or more clients need to receive continuous information from the server.
質問 # 118
You are designing an application for use only during business hours. For the minimum viable product release, you'd like to use a managed product that automatically "scales to zero" so you don't incur costs when there is no activity.
Which primary compute resource should you choose?
- A. Compute Engine
- B. AppEngine flexible environment
- C. Google Kubernetes Engine
- D. Cloud Functions
正解：D
質問 # 119
For this question, refer to the Dress4Win case study.
At Dress4Win, an operations engineer wants to create a tow-cost solution to remotely archive copies of database backup files. The database files are compressed tar files stored in their current data center. How should he proceed?
- A. Create a Cloud Storage Transfer Service job to copy the files to a Regional Storage bucket.
- B. Create a Cloud Storage Transfer Service Job to copy the files to a Coldline Storage bucket.
- C. Create a cron script using gsutil to copy the files to a Regional Storage bucket.
- D. Create a cron script using gsutil to copy the files to a Coldline Storage bucket.
正解：D
解説：
Explanation
Follow these rules of thumb when deciding whether to use gsutil or Storage Transfer Service:
* When transferring data from an on-premises location, use gsutil.
* When transferring data from another cloud storage provider, use Storage Transfer Service.
* Otherwise, evaluate both tools with respect to your specific scenario.
Use this guidance as a starting point. The specific details of your transfer scenario will also help you determine which tool is more appropriate
質問 # 120
You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also to reliably deploy new versions of the application. Which set of steps should you take?
- A. Perform the following:
1) Create a Kubernetes Engine cluster with n1-standard-1 type machines.
2) Build a Docker image from the production branch with all of the dependencies, and tag it with the
3) Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing. - B. Perform the following:
1) Create a managed instance group with n1-standard-1 type machines.
2) Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3) Rebuild the Compute Engine image, and update the instance template to deploy new production releases. - C. Perform the following:
1) Create a managed instance group with f1-micro type machines.
2) Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3) Restart the instances to automatically deploy new production releases. - D. Perform the following:
1) Create a Kubernetes Engine (GKE) cluster with n1-standard-4 type machines.
2) Build a Docker image from the master branch will all of the dependencies, and tag it with "latest".
3) Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to "Always".
Restart the pods to automatically deploy new production releases.
正解：D
解説：
https://cloud.google.com/compute/docs/instance-templates
質問 # 121
For this question, refer to the Mountkirk Games case study.
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way.
How should you design the process?
- A. Create a set of static environments in GCP to test different levels of load - for example, high, medium, and low.
- B. Build stress tests into each component of your application using resources internal to GCP to simulate load.
- C. Create a scalable environment in GCP for simulating production load.
- D. Use the existing infrastructure to test the GCP-based backend at scale.
正解：C
質問 # 122
You are designing a large distributed application with 30 microservices. Each of your distributed microservices needs to connect to a database back-end. You want to store the credentials securely. Where should you store the credentials?
- A. In a config file that has restricted access through ACLs
- B. In a secret management system
- C. In an environment variable
- D. In the source code
正解：C
質問 # 123
For this question, refer to the TerramEarth case study.
TerramEarth's CTO wants to use the raw data from connected vehicles to help identify approximately when a vehicle in the development team to focus their failure. You want to allow analysts to centrally query the vehicle data. Which architecture should you recommend?
A)
B)
C)
D)
- A. Option D
- B. Option B
- C. Option C
- D. Option A
正解：D
解説：
https://cloud.google.com/solutions/iot/
https://cloud.google.com/solutions/designing-connected-vehicle-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion
http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing-connected-car-data
https://cloud.google.com/solutions/iot/
The push endpoint can be a load balancer.
A container cluster can be used.
Cloud Pub/Sub for Stream Analytics
References:
https://cloud.google.com/pubsub/
https://cloud.google.com/solutions/iot/
https://cloud.google.com/solutions/designing-connected-vehicle-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion
http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing-connected-car-data
https://cloud.google.com/solutions/iot/
質問 # 124
You are running a cluster on Kubernetes Engine to serve a web application. Users are reporting that a specific part of the application is not responding anymore. You notice that all pods of your deployment keep restarting after 2 seconds. The application writes logs to standard output. You want to inspect the logs to find the cause of the issue. Which approach can you take?
- A. Connect to the cluster using gcloud credentials and connect to a container in one of the pods to read the logs.
- B. Review the Stackdriver logs for each Compute Engine instance that is serving as a node in the cluster.
- C. Review the Serial Port logs for each Compute Engine instance that is serving as a node in the cluster.
- D. Review the Stackdriver logs for the specific Kubernetes Engine container that is serving the unresponsive part of the application.
正解：D
質問 # 125
For this question, refer to the Dress4Win case study.
Dress4Win has asked you to recommend machine types they should deploy their application servers to. How should you proceed?
- A. Recommend that Dress4Win deploy into production with the smallest instances available, monitor them over time, and scale the machine type up until the desired performance is reached.
- B. Identify the number of virtual cores and RAM associated with the application server virtual machines align them to a custom machine type in the cloud, monitor performance, and scale the machine types up until the desired performance is reached.
- C. Perform a mapping of the on-premises physical hardware cores and RAM to the nearest machine types in the cloud.
- D. Recommend that Dress4Win deploy application servers to machine types that offer the highest RAM to CPU ratio available.
正解：C
質問 # 126
You have an App Engine application that needs to be updated. You want to test the update with production traffic before replacing the current application version.
What should you do?
- A. Deploy the update as a new App Engine application, and use Google's global HTTP load balancing to split traffic between the new and current applications.
- B. Deploy the update in a new VPC, and use Google's global HTTP load balancing to split traffic between the update and current applications.
- C. Deploy the update as a new version in the App Engine application, and split traffic between the new and current versions.
- D. Deploy the update using the Instance Group Updater to create a partial rollout, which allows for canary testing.
正解：A
解説：
Explanation/Reference:
質問 # 127
One of the developers on your team deployed their application in Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.
You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality.
Which two actions should you take? Choose 2 answers.
- A. Remove Python after running pip.
- B. Copy the source after the package dependencies (Python and pip) are installed.
- C. Use larger machine types for your Google Container Engine node pools.
- D. Remove dependencies from requirements.txt.
- E. Use a slimmed-down base image like Alpine linux.
正解：B、E
解説：
Explanation
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU
https://www.alpinelinux.org/about/
質問 # 128
Your web application must comply with the requirements of the European Union's General Data Protection Regulation (GDPR). You are responsible for the technical architecture of your web application. What should you do?
- A. Define a design for the security of data in your web application that meets GDPR requirements.
- B. Ensure that your web application only uses native features and services of Google Cloud Platform, because Google already has various certifications and provides "pass-on" compliance when you use native features.
- C. Enable the relevant GDPR compliance setting within the GCPConsole for each of the services in use within your application.
- D. Ensure that Cloud Security Scanner is part of your test planning strategy in order to pick up any compliance gaps.
正解：C
解説：
Explanation
https://cloud.google.com/security/gdpr/?tab=tab4
Reference: https://www.mobiloud.com/blog/gdpr-compliant-mobile-app/
質問 # 129
Your application needs to process credit card transactions. You want the smallest scope of Payment Card Industry (PCI) compliance without compromising the ability to analyze transactional data and trends relating to which payment methods are used. How should you design your architecture?
- A. Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.
- B. Streamline the audit discovery phase by labeling all of the virtual machines (VMs) that process PCI data.
- C. Create separate projects that only process credit card data.
- D. Create a tokenizer service and store only tokenized data.
- E. Create separate subnetworks and isolate the components that process credit card data.
正解：D
解説：
Reference:
https://www.sans.org/reading-room/whitepapers/compliance/ways-reduce-pci-dss-audit-scope-tokenizing-cardho
質問 # 130
You deploy your custom Java application to Google App Engine.
It fails to deploy and gives you the following stack trace.
What should you do?
- A. Upload missing JAR files and redeploy your application.
- B. Digitally sign all of your JAR files and redeploy your application
正解：B
質問 # 131
Your company is migrating its on-premises data center into the cloud. As part of the migration, you want to integrate Kubernetes Engine for workload orchestration. Parts of your architecture must also be PCI DSS- compliant. Which of the following is most accurate?
- A. App Engine is the only compute platform on GCP that is certified for PCI DSS hosting.
- B. All Google Cloud services are usable because Google Cloud Platform is certified PCI-compliant.
- C. Kubernetes Engine and GCP provide the tools you need to build a PCI DSS-compliant environment.
- D. Kubernetes Engine cannot be used under PCI DSS because it is considered shared hosting.
正解：C
質問 # 132
Your organization has decided to restrict the use of external IP addresses on instances to only approved instances. You want to enforce this requirement across all of your Virtual Private Clouds (VPCs). What should you do?
- A. Remove the default route on all VPCs. Move all approved instances into a new subnet that has a default route to an internet gateway.
- B. Implement a Cloud NAT solution to remove the need for external IP addresses entirely.
- C. Set an Organization Policy with a constraint on constraints/compute.vmExternalIpAccess. List the approved instances in the allowedValues list.
- D. Create a new VPC in custom mode. Create a new subnet for the approved instances, and set a default route to the internet gateway on this new subnet.
正解：C
質問 # 133
A recent audit that a new network was created in Your GCP project. In this network, a GCE instance has an SSH port open the world. You want to discover this network's origin. What should you do?
- A. In the logging section of the console, specify GCE Network as the logging section. Search for the Create Insert entry.
- B. Navigate to the Activity page in the Home section. Set category to Data Access and search for Create VM entry.
- C. Connect to the GCE instance using project SSH Keys. Identify previous logins in system logs, and match these with the project owners list.
- D. Search for Create VM entry in the Stackdriver alerting console.
正解：B
解説：
Company Overview
Mountkirk Games makes online, session-based. multiplayer games for the most popular mobile platforms.
Company Background
Mountkirk Games builds all of their games with some server-side integration and has historically used cloud providers to lease physical servers. A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Mountkirk's current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular.
They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Technical Requirements
Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity.
2. Connect to a managed NoSQL database service.
3. Run customized Linx distro.
Requirements for Game Analytics Platform
1 . Dynamically scale up or down based on game activity.
2. Process incoming data on the fly directly from the game servers.
3. Process data that arrives late because of slow mobile networks.
4. Allow SQL queries to access at least 10 TB of historical data.
5. Process files that are regularly uploaded by users' mobile devices.
6. Use only fully managed services
CEO Statement
Our last successful game did not scale well with our previous cloud provider, resuming in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the gams to target users.
CTO Statement
Our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
CFO Statement
We are not capturing enough user demographic data usage metrics, and other KPIs. As a result, we do not engage the right users. We are not confident that our marketing is targeting the right users, and we are not selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.
質問 # 134
Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings. Which approach should you use?
- A. Configure Stackdriver Monitoring for all Projects, and export to BigQuery.
- B. Grant the security team access to the logs in each Project.
- C. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage.
- D. Configure Stackdriver Monitoring for all Projects with the default retention policies.
正解：C
解説：
Reference:
Overview of storage classes, price, and use cases https://cloud.google.com/storage/docs/storage-classes Why export logs? https://cloud.google.com/logging/docs/export/ StackDriver Quotas and Limits for Monitoring https://cloud.google.com/monitoring/quotas The BigQuery pricing. https://cloud.google.com/bigquery/pricing
質問 # 135
One of the developers on your team deployed their application in Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.
You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality.
Which two actions should you take? Choose 2 answers.
- A. Remove Python after running pip.
- B. Copy the source after the package dependencies (Python and pip) are installed.
- C. Use larger machine types for your Google Container Engine node pools.
- D. Remove dependencies from requirements.txt.
- E. Use a slimmed-down base image like Alpine linux.
正解：B、E
解説：
Explanation
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU
https://www.alpinelinux.org/about/
質問 # 136
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants you to design their new testing strategy. How should the test coverage differ from their existing backends on the other platforms?
- A. Tests should include directly testing the Google Cloud Platform (GCP) infrastructure.
- B. Unit tests are no longer required, only end-to-end tests.
- C. Tests should be applied after the release is in the production environment.
- D. Tests should scale well beyond the prior approaches.
正解：D
解説：
From Scenario:
A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Requirements for Game Analytics Platform include: Dynamically scale up or down based on game activity
質問 # 137
Your company has announced that they will be outsourcing operations functions. You want to allow developers to easily stage new versions of a cloud-based application in the production environment and allow the outsourced operations team to autonomously promote staged versions to production. You want to minimize the operational overhead of the solution. Which Google Cloud product should you migrate to?
- A. Google Kubernetes Engine
- B. Compute Engine
- C. GKE On-Prem
- D. App Engine
正解：A
解説：
Topic 2, Dress4Win case study
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model.
Company Background
Dress4win's application has grown from a few servers in the founder's garage to several hundred servers and appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster, Dress4win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test environments. They are also considering building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
Databases:
MySQL - user data, inventory, static data
Redis - metadata, social graph, caching
Application servers:
Tomcat - Java micro-services
Nginx - static content
Apache Beam - Batch processing
Storage appliances:
iSCSI for VM hosts
Fiber channel SAN - MySQL databases
NAS - image storage, logs, backups
Apache Hadoop/Spark servers:
Data analysis
Real-time trending calculations
MQ servers:
Messaging
Social notifications
Events
Miscellaneous servers:
Jenkins, monitoring, bastion hosts, security scanners
Business Requirements
Build a reliable and reproducible environment with scaled parity of production.
Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud.
Migrate fully to the cloud if all other requirements are met.
Technical Requirements
Evaluate and choose an automation framework for provisioning resources in cloud.
Support failover of the production environment to cloud during an emergency.
Identify production services that can migrate to cloud to save capacity.
Use managed services whenever possible.
Encrypt data on the wire and at rest.
Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a new competitor could use a public cloud platform to offset their up-front investment and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than our current model.
質問 # 138
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